Rover Receiver Internal Differential Corrections for GNSS Accuracy
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Solution Overview
Problem
Existing differential GNSS methods are limited by the need for matching observations between base and rover receivers, leading to the exclusion of non-compatible or non-matching GNSS signals, which reduces accuracy and robustness, especially when mixing different receiver types or constellations, and results in incomplete use of available satellite data.
Innovation Solution
A rover receiver computes internal differential corrections using its own observations, allowing all available observations to be incorporated into the GNSS solution, even if they are not common to the base and rover, thereby enhancing ambiguity resolution and robustness by generating corrections referenced to its own location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional DGNSS methods are used requiring matching observations between base and rover, then differential correction can be applied to common satellites, but non-compatible or non-matching GNSS signals are excluded reducing accuracy and robustness
Solution Approach 1:
The rover receiver computes its own internal differential corrections using its own observations of satellites for which it has matching base observations. This self-service approach allows the rover to generate corrections for all satellites in its view, not just common satellites, thereby improving robustness while maintaining accuracy through self-referenced corrections.
Solution Approach 2:
The system enables the rover to use all available GNSS signals from multiple constellations (GPS, GLONASS, Galileo, Compass) regardless of whether the base receiver observes all the same satellites. The internal correction mechanism makes the system universal by allowing mixed-constellation operation and compatibility with different receiver types.
2Measurement precision
If only common satellite observations are used for differential correction, then external differential corrections can be applied, but incomplete use of available satellite data reduces positioning accuracy
Solution Approach 1:
The system segments satellite observations into two categories: common satellites (used for external differential correction from base) and rover-only satellites (used for internal differential correction). This segmentation allows both types to be processed separately and combined, maximizing the quantity of usable observations while maintaining positioning accuracy through appropriate correction application.
Solution Approach 2:
The rover pre-computes internal differential corrections for rover-only satellites using its own observations before final positioning. This preliminary action ensures that all satellite data is ready for use in the final solution, increasing the number of usable observations without compromising accuracy.
3Adaptability or versatility
If mixed receiver types or constellations are used, then more satellites and observations are available, but receiver capability variations result in inability to use all signals due to lack of matching pairs
Solution Approach 1:
The system dynamically adapts to different receiver capabilities by computing internal corrections based on each receiver's actual observation set. The rover determines which satellites it can observe and generates corrections accordingly, making the system flexible and adaptable to mixed receiver types while maintaining reliability through capability-aware correction generation.
Data Source
AI summary
In the invention, a rover receiver first utilizes data from a base Receiver, a DGNSS reference network, or other differential source to compute a differentially corrected location. Then, using this location and data observed only at the rover, the rover computes an internal set of differential corrections that are stored in computer memory, updated as necessary, and applied in future times to correct observations taken by the rover. The possibly mobile rover receiver, therefore, corrects its own observations with differential corrections computed from its own past observations; relying on external differential for the sole purpose of establishing a reference location, and this is unlike prior art.